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143 7 From Data to Stories: Innovation Patterns in the Six Policy Areas The research methodologies we use shape our thought processes as much as they are shaped by them. Throughout this analysis I have grouped all the HKS Awards semifinalist applications together to create a data set with enough degrees of freedom to support statistical analysis, which would not have been possible had I analyzed the six policy areas separately. And I have consistently conceived of and discussed public sector innovation as a single, though never simple, phenomenon with identifiable characteristics that cross policy areas. It is now time to disaggregate. Public sector innovators in different policy areas confront different types of problems, engage different groups within the population, use different specialist vocabularies, and draw on different bodies of theory and practice . In this chapter I change focus to consider each of the six policy areas defined by the HKS Awards program, identifying and describing the initiatives within each one. This creates an inevitable forest-and-trees dilemma, since 127 semifinalist programs across six policy areas add up to a lot of trees. My solution is to employ both cumulative and comparative approaches. I begin with comparison, delineating how each policy area’s semifinalists differ from the entire set we’ve been considering to this point, using the innovation characteristics presented in chapters 3 to 6 as descriptors. Shifting to a cumulative analysis, I also present the major “themes” evident within each area’s set of innovations—the issues they focus on. An underlying question throughout this analysis is the degree of homogeneity each area displays. Are there a few common foci, or even a single one? Are there discernible trends, or are the areas more internally disparate? Finally, I return to longitudinal comparison and the landscape of public sector innovation as a whole by comparing each policy area’s profile in 2010 to its counterpart in 07-2560-2 CH 7:PWW 2284-7 4/18/14 1:19 PM Page 143 1990–94, noting both changes and continuities. My descriptions of individual programs are of necessity cursory, generally amounting to little more than a thumbnail portrait that scarcely begins to suggest either their achievements or their back stories. Yet I hope that even these brief sketches make it plain that this study has never been dealing with abstractions—that there are flesh-and-blood realities behind each table entry and data point. I hope, too, that I provide sufficient identifying information to enable readers to pursue the initiatives that interest them— my contribution toward diffusion. Many of the programs have their own websites.1 The HKS Awards staff assigned the semifinalist applications to the six policy areas, and I accept both their definition of the policy areas and their assignments of the applicants to them. There are good reasons for doing so beyond convenience . The staff has long-standing familiarity with the policy communities that exist in the public sector in the United States, which gives them a good sense of where a given application fits best. The policy areas they have defined involve some degree of aggregation within an area, and this is necessary if we are to generate any useful generalizations for six areas and only 127 semifinalists. Were I to establish a larger set of policy areas, the number of observations in each policy area would be too small to support general conclusions. We can begin to distinguish among policy areas by the particular populations they engage. Table 7-1 presents the target populations for the six policy areas and compares them to those for all semifinalists. Semifinalists in Management and Governance (MG) predominantly target government bodies and the general population ; those in Transportation, Infrastructure, and Environment (TIE) focus on the general population and on business; those in Community and Economic Development (CED) target business and low-income populations; those in Education and Training (ET) focus on young people and students; those in Health and Social Services (HSS) target high-risk and low-income populations as well as young people; and those in Criminal Justice and Public Safety (CJ) focus on people with dysfunctions. Table 7-1 shows the estimated slopes and intercepts for regressions of the distribution of target groups for each policy area on the distribution of target groups for the entire sample. The results deviate sharply from the pattern in evidence for most of the tables in chapters 3 to 6, with slopes either insignificant or very significantly different from 1...

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